Finding information regarding entities like businesses, organizations, or events in a specific area often means looking through the printed Yellow Pages or searching electronically through search engines or electronic directories and listing services such as Internet Yellow Pages. An example of an Internet Yellow Pages is www.smartpages.com, and an example of a search engine is www.google.com. While useful, printed Yellow Pages have major drawbacks including space limitations that cause the information provided to be limited, as well as publishing frequency limits which limit how up to date the information can be. For example, the printed Yellow Pages are not useful for printing news regarding a weekend special or daily menu items for a restaurant.
On the Internet, a business can provide more information on its web site than it is able to in the printed Yellow Pages as well as update it as frequently as necessary. However, finding a web site for a specific business can be difficult, especially for local businesses that may not have an easily remembered web address or an easily searchable name. For example, a restaurant named “Best Cuisine” located in Boston, Mass. contains such generic terms in its name that a search containing “best cuisine” and “Boston” is unlikely to find the web site for the restaurant. Finding categories of businesses on the Internet (particularly for local businesses) is also problematic. Internet search engines attempt to help find this information, but, using them usually requires a multi-step process that often does not result in relevant information. Finding information regarding businesses at a specific location in a search engine entails assembling a list of relevant keywords and a geographic locator. For instance, if one were searching for a business that sells tennis rackets in Boston, Mass., one could type in “tennis racket”, and “Boston” in the search box. The problem with performing this type of search on a search engine is that the result may include noncommercial results such as articles regarding tennis rackets or tennis organizations in Boston, rather than a business that sells the product. The result may also encompass a business that sells tennis rackets but does not have a physical location or a business with a physical location in a different state or in the same state but very far away. This is not useful for users who want to go to a nearby store and buy the tennis racket immediately.
Finding information regarding a business in Internet Yellow Pages entails typing in a location and guessing a category that the desired businesses may fall into. For instance, in our example above, one may type in “tennis store” for a category. Depending on the directory, the search may or may not return relevant results. If the search does not return a relevant result, than one would have to perform the search again, possibly trying a different category like “sporting goods.”
Another shortcoming of the prior art approaches to finding information regarding local businesses is that none of the methods discussed above allows one to browse multiple types of businesses in a desired radius. For instance, a user may wish to plan an evening shopping trip by looking for information on restaurants, gift shops, and clothing stores on or near Newbury Street in Boston, Mass. Doing this type of search would entail multiple searches in the printed Yellow Pages, search engines, and Internet Yellow Pages. In this example, the most relevant criteria for choosing the stores to visit and a restaurant might be distance of the businesses from each other and the hours of operation. This type of search is quite difficult to perform in the printed Yellow Pages because searching for a business based on distance is not possible in the printed Yellow Pages since only an address, and not a map or a radius, is given for a business listing. This type of search would also be a particularly difficult query to do with a traditional search engine or on an Internet Yellow Pages site. It would require performing a separate search for clothing stores, gift shops, and restaurants at the desired address or street; examining each set of search results for relevant matches (such as clothing type, type of gifts desired, and type of cuisine); re-doing any searches that do not return relevant results; searching through the relevant results for each one's business hours; determining whether the gift shops, clothing stores, and restaurants found are open during desired hours; determining whether the gift shops, clothing stores, and restaurants found are within walking distance of each other, and performing more searches if one business is not within walking distance of the others; taking notes on the results as they are found in order to use later (or opening many confusing web browser windows); and finally combining all the results into a reasonable set of businesses at the end.
Another shortcoming of the prior art approaches is that it would be very difficult for a user to find all the businesses in a particular section of a city. For example, if the user will be staying at a hotel on Fifth Avenue in New York and would like to know about all of the businesses on the same block as the hotel, the traditional approaches do not enable the user to find such businesses. Listings in the Printed Yellow Pages are organized alphabetically or by categories so finding all the businesses in one block of Fifth Avenue would be quite a difficult task. Performing such a search on a traditional search engine is also quite difficult, given that a geographic locator, such as “Fifth Avenue” and “New York” would have to be entered into the search box, but limiting the geography to a certain block in Fifth Avenue is not possible on the traditional search engine. Internet Yellow Pages allow a user to search by radius, so for example, a user can enter a street number on Fifth Avenue and perform desired searches, but since searches on an Internet Yellow Pages site are based on categories, the user would have to perform a separate search for all the categories that the user may be interested in (e.g., women's apparel, accessories, children's apparel, gift shops, restaurants . . . etc.). Furthermore, searches are based on a radius in Internet Yellow Pages, so that such searches would include results on other streets or other neighborhoods in the vicinity which may be in areas the user is not interested in visiting.
As discussed above, the hours of operation for a business is a common source of questions regarding local businesses. Users would like to be sure that a business will be open when they get there before they make a trip to it. Many business include their operating hours in their printed or Internet Yellow Pages or web site listings, but these are textual listings of the hours and can be hard to find. On the Internet, a user would have to find the web site or a listing of a business by performing a search on a search engine or an Internet Yellow Pages, click on the listing or web site, then find the right link to display the operating hours. Even after the hours are found, it requires a bit of time and thought to find the correct hours of operation for the current day and time, and see if the business is currently open. In particular, this mental computation is impractical when one wants to quickly glance through a list of tens or hundreds of businesses to see which one is open now, as might happen if you urgently need to purchase something late at night or on a holiday. Also, listings in printed Yellow Pages or online web sites often make no mention of special holiday hours, vacations, or temporary closings or hours changes. Often, it is during these situations when consumers need operating hours information the most.
A similar problem exists whenever a user needs to search through multiple entities for any single piece of information, such as searching through all the hotels in a certain neighborhood to find those that have a current vacancy. Other examples include finding one of the many stores within walking distance of one's home that sells a particular brand of phone, finding the businesses among all the businesses within the user's town that are hiring a cashier, finding all the movies in movie theaters that are within a half hour drive that will be playing between 45 minutes to 1½ hours from now, finding the homes within a particular neighborhood that are having an open house or a garage sale tomorrow, finding the apartment complexes among all the apartment complexes in a certain neighborhood that have apartments available, or finding all the parks in a town that are currently having a concert. This problem also applies to combinations of information, such as finding all the stores in the neighborhood with a particular phone in stock that is currently open. All of these searches can be difficult or time-consuming with existing approaches.
Other shortcomings of prior art approaches include their methods of presentation. Searches for entity information, even seemingly simple searches, can produce large amounts of result data. Some example data include names, pictures, distances, product and service availability, and operating hours. Presentation methods that can communicate large amounts of complex data in a simple manner are desirable. However, pages filled with textual listings to click on are still the typical results from current search engines and Internet Yellow Pages. Also, even though search results may include large amounts of data, it can be unclear to a user which pages or data were searched to find the results. For example, a user who is aware of a nearby tennis store may attempt to look up its hours in an Internet Yellow Pages, but find that the store does not appear in the results. Does this mean that the store is not present in the directory, or that perhaps the category searched under (e.g., sporting goods) was wrong? It would be advantageous to communicate to the user which entities were searched to find the answer, while still keeping the matching results easily comprehensible.
In light of the foregoing complexity, one can see why it is desirable to provide systems or methods to make finding information about entities easier.